The present invention generally relates to inspection in a semiconductor manufacturing process and in particular to using an inspection system to inspect for defects in a circuit pattern on a semiconductor material. The circuit pattern may include, a Liquid Crystal Diode (LCD) display, a Thin Film Transistor (TFT) display, a memory matte, an integrated circuit, a photomask, a magnetic head, and the like. The inspection system may include a Semiconductor Electron Microscope (SEM) detection system, an optical detection system, a X-ray detection system, a Focus Beam Ion detection system, a Transparent Electron Microscope (TEM) detector system, a particle detection system, and the like.
FIG. 1 shows a simplified layout of a semiconductor wafer 100 which is a target of an inspection system. There are many die, for example, 110, 112, and 114 on the wafer 100. Normally each die has the same pattern on the wafer 100 for use in the same product.
FIGS. 2 and 3 each show a conventional inspection system (an example is given in U.S. Pat. No. 5,502,306, “Electron Beam Inspection System and Method,” by Meisburger, et. al., issued Mar. 26, 1996. Another example is given in U.S. Pat. No. 6,087,673, “Method for Inspecting Pattern and Apparatus Thereof,” by Shishido, et. al., issued Jul. 11, 2000) In the conventional system, a SEM Detecting Apparatus 208 is connected to an Image Processing System 228. The SEM Detecting Apparatus includes, an electron beam 210 from an electron source 212 sending electrons to a wafer 100 through an objective lens 214. The secondary electron emissions 216 from the wafer 100 are detected by a sensor 218. A beam deflector 220 causes the electron beam 210 to scan horizontally, while stage 222 movement causes a vertical scan. Thus a two dimensional (x-y) image is obtained. The resulting analog sensor signals are converted to digital data and this two-dimensional digital image is sent to Image Processing System 228 for defect detection.
In the Image Processing System 228 the first digital image is stored as a reference image. Another scan of a different potion of the wafer, produces a second digital image. This second image is the inspection image which may or may not be stored, and is compared with the reference image. As the two images are presumed to have the same pattern, a difference image is formed. The difference image is thresholded with an initial threshold, and when a defect image exists, a defect is determined to exist. Defect information such as defect position (x-y coordinates), size (area), x-projection size, and y-projection size is also generated. The defect information forms an entry in a defect list 232. The above process is repeated with the inspection image, i.e., second digital image, being stored as the reference image and overwriting the stored first digital image. A newly scanned image, i.e., third digital image, is the new inspection image and replaces the second digital image. The result of this repetitive process is a defect list 232. This defect list 232 is sent by the Image Processing System 228 to a Graphic User Interface (GUI) Console 230 for verification by the user. If the user desires to view a defect in the defect list 232, the positional information is used to re-scan the defect area and show the defect on the console 230.
The conventional Image Processing System 228 normally operates in one and only one of two detection modes at a time. One is a die to die comparison mode 234 (FIG. 2) and the other is an array comparison mode 236 (FIG. 3). The die to die comparison 234 compares one die image with the next die image, where each die belongs to the same product. Array comparison 236 compares a repeated pattern in, for example, a memory matte, on a die. Thus the conventional image processing system has a problem in that a mixture of die to die comparison and array comparison cannot be done in one scan of the wafer.
In the conventional system determining the threshold to be used in the difference images during actual inspection of the wafer 100 is very important. Since the defect image is determined from thresholding the difference image, too low a threshold may cause many false defects. Too high a threshold may miss many actual defects. Thus setting up the threshold is an important part of the inspection process.
FIG. 4 shows a conventional threshold setup method. At step 310 the user sets a value for the initial threshold based on the user's best guess as to the maximum noise level in the images. The initial threshold is typically set low and is raised to a higher value when applying this setup method. The user also selects a small region of the wafer for trial inspection. The conventional system, using the initial threshold, determines a defect list 232, including defect information (step 320), which is sent to the Graphical User Interface (GUI) console 230 for user evaluation. At step 330, the defect information is used to re-scan the defect locations on the wafer 100 and display the defects for verification. The user then verifies whether the defects are true or false defects. At step 340, if there are too few true defects or too many false defects, the user sets a new higher threshold, and the system goes back to step 310. Typically this loop must be repeated one to three times, before a final threshold is determined. In FIG. 4 user operation is indicated by a bold box 360. Thus step 310 and 330 involve user operation 360. This threshold setup method has several problems. First it is slow and manually intensive. Since defect images are not stored, rescanning is necessary to view the defect list 232 for verification. As scanning requires wafer stage 222 movement, this process takes time. If the user determines that the threshold is too low, the user must guess at a new level. The results of the threshold modification are available only after the small region is re-scanned during a second trial inspection. The above process is repeated several times and is slow. Another problem is that the repetitive re-scanning of the wafer 100 could alter the wafer surface and hence the inspection results. Lastly, no image data is retained for use in actual inspection or follow-up analysis, thus it is difficult to improve the process.
Therefore there is a need for a defect inspection method and system that is faster and more efficient. There is also a need for maintaining defect image data for use in, for example, trial inspection, defect analysis, actual inspection, and/or after inspection analysis.